INFO 2950: Mathematical Methods for Information Science

Teaches basic mathematical methods for information science. Topics include graph theory, discrete probability, Bayesian methods, finite automata, Markov models, and hidden Markov models. Uses examples and applications from various areas of information science such as the structure of the web, genomics, natural language processing, and signal processing.

Offered: Spring

Prerequisites: Corequisite: MATH 2310 or equivalent

Grade Options: let or S/U

Credit Hours: 4 credit.

Website: INFO 2950